In the integrated circuit industry, electron microscopes are central to microstructural analysis of integrated circuit components. The quality of a finished integrated circuit is highly dependent on the measurement and control of the circuit's critical dimensions. Thus, it is very important to ensure that critical dimension measurements received from metrology tools, such as electron microscopes, are precise and accurate. Typically, in critical dimension analysis of an integrated circuit component an electron microscope measures the apparent width of a structure when determining its dimensions. The apparent width of the structure is compared to critical dimension specifications in order to determine the compliance of the integrated circuit component.
Unfortunately, there are disadvantages to using the typical apparatus and method, as the apparent width of a structure as reported by the measurement tool is often different from the actual width of the structure. In addition, the discrepancy between the actual width and the apparent width of the structure could fluctuate from day to day, as well as from tool to tool. Thus, the integrity of the data derived from such measurements is often called into question, and is difficult to rely on.
In an effort to overcome this problem, it is possible to use a calibration piece having a structure with a known size. The calibration piece is loaded into the measurement tool and measured at regular intervals, such as once each day. The difference between the apparent width and the actual width of the structure on the calibration piece is used as a correction factor for other measurements. Unfortunately, even this procedure tends to not have the desired accuracy in all situations.
Similarly, calibration pieces have been used that are optimized for viewing on an electron microscope, such as tin-on-gold resolution standards. These are used to verify the proper functioning of the electron microscope, and to measure the inherent resolution of the electron microscope. Unfortunately, because the interaction between the electron beam and the calibration piece is very different on such standards in comparison with the interaction between the electron beam and the semiconductor samples to be measured, the data produced is unfortunately of limited use in calibrating the scanning electron microscope for use as a measurement tool.
There have been attempts to take into account the effects the interaction between the electron beam and sample when making measurements. For example, commonly-assigned U.S. Pat. No. 6,770,868 describes measurement techniques using calibration standards with known metrics. A calibration factor for the measurement tool is computed by comparing the first measurement to the first known metric. A structure on the sample is then measured using a measurement tool to produce a precursor measurement. This precursor measurement is adjusted with the calibration factor to produce an intermediate measurement. Then the intermediate measurement is adjusted with the sample composition data to produce the actual measurement. Thus, rather than naively processing the scan data from the measurement tool (e.g., an electron microscope) to produce a measurement result, a model is applied that takes into account (1) how the electron optics perform, including their deviations from ideality, and (2) how the incident electrons interact with the structure on the sample to produce secondary and backscattered electrons. The properties of the electron optical system can be derived from both an analytical model of the optical system and from the measurement data taken on the calibration standard. The actual physical properties of the sample can then be determined using an analytical model of the interaction of the incident beam with the sample and the properties of the electron optical system as determined above.
Such a system can improve measurement data somewhat by correcting the apparent width of a structure by both a calibration factor, which accounts for any drift in the properties of the measurement tool, and by sample structural and composition data, which accounts for measurement differences due to different materials and structures being measured. By calibrating the measurement tool in this manner, the precision and accuracy of the measurement tool is improved. Unfortunately, such systems use calibration standards of a similar composition of the structure to be measured, in order to provide correct measurements of structures consisting of a wide range of materials. These calibration standards are not sufficiently generic that they can be easily used for different types of samples.
Furthermore, it is often desirable to measure the same sample or sets of similar samples with two or more different tools. In order to properly compare the measurements made with different tools, each tool's parameters must be calibrated and modeled as described above. To properly model the tools, the same calibration standard must be used to model the behavior of each tool. This can be particularly inconvenient if the tools are in different locations that are separated from each other by large distances.
Thus, there is a need in the art for a standard that overcomes these drawbacks and a technique for extracting tool parameters and performing tool matching with such standards.